/semantic-node-build

tools:
  - read
  - write
  - edit
  - grep
arguments: $TOPIC

Semantic Node Builder

Create and record semantic nodes in the active WFGY tree to capture reasoning insights and maintain memory.

Based on the WFGY project: https://github.com/onestardao/WFGY

Instructions

1. **Prepare Node Context**

• Parse topic from "$TOPIC" or auto-detect from context
• Read active tree from `.wfgy/trees/active_tree.json`
• Load previous node for reference
• Get current context from `.wfgy/context.json`

2. **Calculate Semantic Metrics**

• Generate embedding for current topic
• Compare with previous node embedding
• Calculate ΔS (semantic tension): ΔS = 1 - cos(θ)
• Determine λ_observe (logic direction):
• → (convergent): Building on previous (ΔS < 0.4)
• ← (divergent): New direction (ΔS > 0.6)
• <> (recursive): Returning to earlier (pattern match)
• × (chaotic): Unstable (ΔS > 0.9)
• Calculate E_resonance (stability measure)

3. **Identify Active Module**

• Analyze which WFGY module is primary:
• BBMC: If minimizing residue
• BBPF: If exploring multiple paths
• BBCR: If recovering from failure
• BBAM: If optimizing attention
• Record module attribution for traceability

4. **Build Node Structure**

   {
     "id": "node_[timestamp]_[hash]",
     "timestamp": "ISO_8601",
     "topic": "$TOPIC",
     "module": "BBMC|BBPF|BBCR|BBAM",
     "metrics": {
       "deltaS": 0.XX,
       "lambda": "→|←|<>|×",
       "e_resonance": 0.XX,
       "confidence": 0.XX
     },
     "content": {
       "insight": "Encoded reasoning conclusion",
       "context": "Surrounding context",
       "keywords": ["key1", "key2", "key3"]
     },
     "relationships": {
       "parent_id": "previous_node_id",
       "references": [],
       "bridges_to": []
     }
   }

5. **Apply Recording Logic**

• Check recording criteria:
• Primary: ΔS > 0.6 (always record)
• Secondary: ΔS ∈ [0.4, 0.6] AND λ ∈ {←, <>}
• Forced: User explicitly requests
• If criteria met:
• Append node to tree
• Update tree metadata
• Create cross-references
• Update indices

6. **Post-Processing**

• Update tree statistics:
• Increment node_count
• Update total_deltaS
• Recalculate avg_deltaS
• Track max_depth
• Check for patterns:
• Detect loops (recursive patterns)
• Identify clusters (related nodes)
• Find bridges (connection points)
• Trigger compression if node_count > threshold
• Update `.wfgy/context.json`

Output Format

✓ Semantic Node Recorded
═══════════════════════════════════════
Node ID: [node_id]
Topic: $TOPIC
Timestamp: [ISO_8601]

Metrics:
- ΔS (Tension): [value] [Low/Medium/High]
- λ (Direction): [symbol] [convergent/divergent/recursive]
- E (Resonance): [value]
- Confidence: [percentage]%

Module Used: [BBMC/BBPF/BBCR/BBAM]
Insight: [encoded reasoning]

Tree Status:
- Active Tree: [tree_name]
- Total Nodes: [count]
- Avg Tension: [value]
- Memory Usage: [size]

Related Nodes:
• [Previous topic] (ΔS: [value])
• [Related topic] (ΔS: [value])

Recording Patterns

Common node types:

• **Insight Nodes**: Major realizations (high ΔS)
• **Bridge Nodes**: Connections between concepts
• **Checkpoint Nodes**: Stable states for recovery
• **Decision Nodes**: Choice points in reasoning
• **Error Nodes**: Failed paths (for learning)

Integration

Works with:

• `/wfgy:formula-all` for comprehensive analysis
• `/semantic:tree-view` to see node in context
• `/boundary:detect` to check knowledge limits
• `/memory:compress` when tree gets large